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Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction

Molecular Biology and Evolution(2020)10.1093/molbev/msaa047Source: DataRank Database

Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction is a research paper published in Molecular Biology and Evolution (2020). On theSindex it has a DataRank of 0. It has been cited 1 time.

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (11 grants)Impact (FWCI 0.03)OA: hybridTopics (69)Linked Datasets (2)DataCite Reuse (2)IDs (PubMed, PMC, OpenAlex)SDGs (2)

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Context only (not used in score)

Findable (2/2)

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Accessible (1/2)

Open Access

Interoperable (2/2)

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Authors (5)

Philippe Lemey ORCID,Marc A. Suchard ORCID,Andrew Rambaut ORCID,Guy Baele ORCID,Mandev S. Gill ORCID

Live enrichment

PubMed:32101295 PMC:PMC7253210 OpenAlex:https://openalex.org/W3003652671

Wellcome Trust

Grant: 206298/Z/17/Z

NIAID NIH HHS

Grant: R01 AI107034

NIAID NIH HHS

Grant: U19 AI135995

European Commission

Grant: 725422

The evolutionary dynamics of pathogen emergence and establishment: from Reservoir Detection to Outbreak Control

National Institutes of Health

Grant: 3U19AI135995-04S3

Consortium for Viral Systems Biology (CViSB)

National Science Foundation

Grant: 1264153

Advancing the Molecular Epidemiology of Infectious Diseases through Bayesian Phylogenetics

National Institutes of Health

Grant: 5R01AI107034-05

BAYESIAN MODELING AND DATA INTEGRATION IN INFECTIOUS DISEASE PHYLODYNAMICS

National Institutes of Health

Grant: 3U19AI135995-03S1

Consortium for Viral Systems Biology (CViSB)

Wellcome Trust

Grant: 206298

Putting genomic surveillance at the heart of viral epidemic response.

Wellcome Trust

FWCI

0.03

Citation Percentile

0.3%

Influential Citations

Citation Trend

2020

hybridLicense: cc-by

journalhttps://doi.org/10.1093/molbev/msaa047

HYBRIDhttps://doi.org/10.1093/molbev/msaa047

publisherhttps://doi.org/10.1093/molbev/msaa047

publisherhttp://academic.oup.com/mbe/advance-article-pdf/doi/10.1093/molbev/msaa047/32931970/msaa047.pdf

publisherhttp://academic.oup.com/mbe/article-pdf/37/6/1832/33317171/msaa047.pdf

Fields of Study

COVID-19 epidemiological studiesData-Driven Disease SurveillanceGenomics and Phylogenetic StudiesMedicineBiologyComputer ScienceMathematicsEnvironmental Science0301 basic medicine03 medical and health sciencesAfrica, WesternBayes TheoremGenetic TechniquesHemorrhagic Fever, EbolaPhylogenySoftware

MeSH Terms

Africa, WesternBayes TheoremGenetic TechniquesPhylogenySoftwareHemorrhagic Fever, Ebola

Keywords

InferencePosterior probabilityComputer scienceBayesian probabilityBayesian inferenceData miningSet (abstract data type)Phylogenetic treeMarkov chain Monte CarloMachine learningArtificial intelligenceBiologyBeastBayesian PhylogeneticsReal-time AnalysisPathogen PhylodynamicsOnline InferenceFOS: Computer and information sciences570330q-bio.PEBioengineeringMethodology (stat.ME)2.5 Research design and methodologies (aetiology)GeneticsAetiologyQuantitative Biology - Populations and EvolutionStatistics - MethodologyPhylogenyEvolutionary BiologyPopulations and Evolution (q-bio.PE)Bayes TheoremHemorrhagic Fever, EbolaResourcesAfrica, WesternInfectious DiseasesGood Health and Well BeingGenetic Techniquesstat.MEFOS: Biological sciencesAfricaEbolaHemorrhagic FeverBiochemistry and Cell BiologyInfectionWesternSoftware

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being

Additional file 1 of Genofunc: genome annotation and identification of genome features for automated pipelining analysis of virus whole genome sequences

10.6084/m9.figshare.23265173.v1figshare

Additional file 1 of Genofunc: genome annotation and identification of genome features for automated pipelining analysis of virus whole genome sequences

10.6084/m9.figshare.23265173figshare